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2019 | OriginalPaper | Buchkapitel

Atlas of Acceleration-Induced Brain Deformation from Measurements In Vivo

verfasst von : Arnold D. Gomez, Andrew Knutsen, Deva Chan, Yuan-Chiao Lu, Dzung L. Pham, Philip Bayly, Jerry L. Prince

Erschienen in: Computational Biomechanics for Medicine

Verlag: Springer International Publishing

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Abstract

In traumatic brain injury (TBI), rapid head acceleration resulting from a blow or fall results in detrimental brain tissue deformation. These types of injuries are frequent and can have devastating effects. Understanding the relationship between acceleration and deformation is a challenging and essential step towards designing effective preventive strategies. This study describes patterns of acceleration-induced brain deformation in a group of human volunteers (n = 7). Unlike previous research, the analysis herein involved spatiotemporal analysis of 3D kinematics. In each subject, tagged magnetic resonance imaging (MRI) was acquired during a mild acceleration event, and displacements were extracted using a mechanically regularized motion estimation algorithm. This technique involved registering an anatomical template (a finite-element mesh) to all of the subjects allowing translation of scalar strain projections back to the template to be averaged. Our results show that, in individuals, weighting acceleration measurements by the subject’s brain volume improves the correlation between acceleration magnitude and deformation (R 2 of 0.66 in the weighted comparison, compared to 0.34). In individuals, and the group, brain deformation peaked after the peak acceleration, and near the interface between the brain and the skull. However, some deformation was also observed near medial brain structures, which supports the idea that the falx plays a role in transferring mechanical power to the middle of the brain.

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Literatur
1.
Zurück zum Zitat Shaw NA (2002) The neurophysiology of concussion. Prog Neurobiol 67:281–344CrossRef Shaw NA (2002) The neurophysiology of concussion. Prog Neurobiol 67:281–344CrossRef
2.
Zurück zum Zitat Siedler DG, Chuah MI, Kirkcaldie MTK, Vickers JC, King AE (2014) Diffuse axonal injury in brain trauma: insights from alterations in neurofilaments. Front Cell Neurosci 8:429CrossRef Siedler DG, Chuah MI, Kirkcaldie MTK, Vickers JC, King AE (2014) Diffuse axonal injury in brain trauma: insights from alterations in neurofilaments. Front Cell Neurosci 8:429CrossRef
3.
Zurück zum Zitat Dickie DA, Shenkin SD, Anblagan D, Lee J, Blesa Cabez M, Rodriguez D, Boardman JP, Waldman A, Job DE, Wardlaw JM (2017) Whole brain magnetic resonance image atlases: a systematic review of existing atlases and caveats for use in population imaging. Front Neuroinform 11:1CrossRef Dickie DA, Shenkin SD, Anblagan D, Lee J, Blesa Cabez M, Rodriguez D, Boardman JP, Waldman A, Job DE, Wardlaw JM (2017) Whole brain magnetic resonance image atlases: a systematic review of existing atlases and caveats for use in population imaging. Front Neuroinform 11:1CrossRef
4.
Zurück zum Zitat Ibrahim E-SH (2011) Myocardial tagging by cardiovascular magnetic resonance: evolution of techniques-pulse sequences, analysis algorithms, and applications. J Cardiovasc Magn Reson 13:36CrossRef Ibrahim E-SH (2011) Myocardial tagging by cardiovascular magnetic resonance: evolution of techniques-pulse sequences, analysis algorithms, and applications. J Cardiovasc Magn Reson 13:36CrossRef
5.
Zurück zum Zitat Abney TM, Feng Y, Pless R, Okamoto RJ, Genin GM, Bayly PV (2011) Principal component analysis of dynamic relative displacement fields estimated from MR images. PLoS One 6:e22063CrossRef Abney TM, Feng Y, Pless R, Okamoto RJ, Genin GM, Bayly PV (2011) Principal component analysis of dynamic relative displacement fields estimated from MR images. PLoS One 6:e22063CrossRef
6.
Zurück zum Zitat Laksari K, Wu LC, Kurt M, Kuo C, Camarillo DC (2015) Resonance of human brain under head acceleration. J R Soc Interface 12:331CrossRef Laksari K, Wu LC, Kurt M, Kuo C, Camarillo DC (2015) Resonance of human brain under head acceleration. J R Soc Interface 12:331CrossRef
7.
Zurück zum Zitat Peng H, Orlichenko A, Dawe RJ, Agam G, Zhang S, Arfanakis K (2009) Development of a human brain diffusion tensor template. NeuroImage 46:967–980CrossRef Peng H, Orlichenko A, Dawe RJ, Agam G, Zhang S, Arfanakis K (2009) Development of a human brain diffusion tensor template. NeuroImage 46:967–980CrossRef
8.
Zurück zum Zitat Bai W, Shi W, de Marvao A, Dawes TJW, O’Regan DP, Cook SA, Rueckert D (2015) A bi-ventricular cardiac atlas built from 1000+ high resolution MR images of healthy subjects and an analysis of shape and motion. Med Image Anal 26:133–145CrossRef Bai W, Shi W, de Marvao A, Dawes TJW, O’Regan DP, Cook SA, Rueckert D (2015) A bi-ventricular cardiac atlas built from 1000+ high resolution MR images of healthy subjects and an analysis of shape and motion. Med Image Anal 26:133–145CrossRef
9.
Zurück zum Zitat Subsol G, Roberts N, Doran M, Thirion JP, Whitehouse GH (1997) Automatic analysis of cerebral atrophy. Magn Reson Imaging 15:917–927CrossRef Subsol G, Roberts N, Doran M, Thirion JP, Whitehouse GH (1997) Automatic analysis of cerebral atrophy. Magn Reson Imaging 15:917–927CrossRef
10.
Zurück zum Zitat Knutsen AK, Magrath E, McEntee JE, Xing F, Prince JL, Bayly PV, Butman JA, Pham DL (2014) Improved measurement of brain deformation during mild head acceleration using a novel tagged MRI sequence. J Biomech 47:3475–3481CrossRef Knutsen AK, Magrath E, McEntee JE, Xing F, Prince JL, Bayly PV, Butman JA, Pham DL (2014) Improved measurement of brain deformation during mild head acceleration using a novel tagged MRI sequence. J Biomech 47:3475–3481CrossRef
11.
Zurück zum Zitat Gomez AD, Xing F, Chan D, Pham D, Prince J (2017) Motion estimation with finite-element biomechanical models and tracking constraints from tagged MRI. In: Wittek A, Joldes G, Nielsen PMF, Doyle BJ, Miller K (eds) Computational biomechanics for medicine. Springer, Cham, pp 81–90CrossRef Gomez AD, Xing F, Chan D, Pham D, Prince J (2017) Motion estimation with finite-element biomechanical models and tracking constraints from tagged MRI. In: Wittek A, Joldes G, Nielsen PMF, Doyle BJ, Miller K (eds) Computational biomechanics for medicine. Springer, Cham, pp 81–90CrossRef
12.
Zurück zum Zitat Collins DL, Zijdenbos AP, Kollokian V, Sled JG, Kabani NJ, Holmes CJ, Evans AC (1998) Design and construction of a realistic digital brain phantom. IEEE Trans Med Imaging 17: 463–468CrossRef Collins DL, Zijdenbos AP, Kollokian V, Sled JG, Kabani NJ, Holmes CJ, Evans AC (1998) Design and construction of a realistic digital brain phantom. IEEE Trans Med Imaging 17: 463–468CrossRef
13.
Zurück zum Zitat Roy S, Carass A, Prince JL, Pham DL (2014) Mach Learn Med Imaging 8679:248–255CrossRef Roy S, Carass A, Prince JL, Pham DL (2014) Mach Learn Med Imaging 8679:248–255CrossRef
14.
Zurück zum Zitat Kroon D-J (2011) Segmentation of the mandibular canal in cone-beam CT data. Doctoral Dissertation, University of Twente, Enschede, Netherlands. isbn:978-90-365-3280-8 Kroon D-J (2011) Segmentation of the mandibular canal in cone-beam CT data. Doctoral Dissertation, University of Twente, Enschede, Netherlands. isbn:978-90-365-3280-8
15.
Zurück zum Zitat Tobon-Gomez C, De Craene M, McLeod K, Tautz L, Shi W, Hennemuth A, Prakosa A, Wang H, Carr-White G, Kapetanakis S, Lutz A, Rasche V, Schaeffter T, Butakoff C, Friman O, Mansi T, Sermesant M, Zhuang X, Ourselin S, Peitgen HO, Pennec X, Razavi R, Rueckert D, Frangi AF, Rhode KS (2013) Benchmarking framework for myocardial tracking and deformation algorithms: an open access database. Med Image Anal 17:632–648CrossRef Tobon-Gomez C, De Craene M, McLeod K, Tautz L, Shi W, Hennemuth A, Prakosa A, Wang H, Carr-White G, Kapetanakis S, Lutz A, Rasche V, Schaeffter T, Butakoff C, Friman O, Mansi T, Sermesant M, Zhuang X, Ourselin S, Peitgen HO, Pennec X, Razavi R, Rueckert D, Frangi AF, Rhode KS (2013) Benchmarking framework for myocardial tracking and deformation algorithms: an open access database. Med Image Anal 17:632–648CrossRef
16.
Zurück zum Zitat Vadakkumpadan F, Arevalo H, Ceritoglu C, Miller M, Trayanova N (2012) Image-based estimation of ventricular fiber orientations for personalized modeling of cardiac electrophysiology. IEEE Trans Med Imaging 31:1051–1060CrossRef Vadakkumpadan F, Arevalo H, Ceritoglu C, Miller M, Trayanova N (2012) Image-based estimation of ventricular fiber orientations for personalized modeling of cardiac electrophysiology. IEEE Trans Med Imaging 31:1051–1060CrossRef
17.
Zurück zum Zitat Spencer AJM (1985) Continuum mechanics. Dover, New YorkMATH Spencer AJM (1985) Continuum mechanics. Dover, New YorkMATH
18.
Zurück zum Zitat Zhang L, Yang KH, King AI (2004) A proposed injury threshold for mild traumatic brain injury. J Biomech Eng 126:226–236CrossRef Zhang L, Yang KH, King AI (2004) A proposed injury threshold for mild traumatic brain injury. J Biomech Eng 126:226–236CrossRef
19.
Zurück zum Zitat Alexander DC, Pierpaoli C, Basser PJ, Gee JC (2001) Spatial transformations of diffusion tensor magnetic resonance images. IEEE Trans Med Imaging 20:1131–1139CrossRef Alexander DC, Pierpaoli C, Basser PJ, Gee JC (2001) Spatial transformations of diffusion tensor magnetic resonance images. IEEE Trans Med Imaging 20:1131–1139CrossRef
20.
Zurück zum Zitat Kumaresan S, Radhakrishnan S (1996) Importance of partitioning membranes of the brain and the influence of the neck in head injury modelling. Med Biol Eng Comput 34:27–32CrossRef Kumaresan S, Radhakrishnan S (1996) Importance of partitioning membranes of the brain and the influence of the neck in head injury modelling. Med Biol Eng Comput 34:27–32CrossRef
21.
Zurück zum Zitat Monea AG, Verpoest I, Vander Sloten J, Van der Perre G, Goffin J, Depreitere B (2012) Assessment of relative brain-skull motion in quasistatic circumstances by MR imaging. J Neurotrauma 29:2305–2317CrossRef Monea AG, Verpoest I, Vander Sloten J, Van der Perre G, Goffin J, Depreitere B (2012) Assessment of relative brain-skull motion in quasistatic circumstances by MR imaging. J Neurotrauma 29:2305–2317CrossRef
Metadaten
Titel
Atlas of Acceleration-Induced Brain Deformation from Measurements In Vivo
verfasst von
Arnold D. Gomez
Andrew Knutsen
Deva Chan
Yuan-Chiao Lu
Dzung L. Pham
Philip Bayly
Jerry L. Prince
Copyright-Jahr
2019
DOI
https://doi.org/10.1007/978-3-319-75589-2_2

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